Product design question
How would you design Facebook Dating?
- Meta
- Product design
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Product sense for a trust-sensitive, two-sided matching product inside an existing social graph.
How to approach it
- Clarify the target: singles within an existing user base, differentiated from standalone dating apps by social context.
- Identify pain points: safety and catfishing concerns, low-quality matches, and privacy from existing friends.
- Propose an opt-in separate profile, matching via shared interests, groups, or events, and mutual-friend transparency as a trust signal.
- Prioritize the safety and privacy separation first, since it's the biggest adoption blocker.
- Define success as mutual matches that lead to an off-app conversation.
- Note what data you'd need consent for before using it in matching.
What a strong answer includes
- Leverages the platform's unique asset, existing social graph and interests, as differentiation versus standalone dating apps.
- Names the privacy tension explicitly: dating activity must stay invisible to the person's regular friend list.
- Proposes a concrete trust feature, e.g. optional mutual-friend visibility to reduce catfishing risk.
- Picks a quality metric, matches leading to real conversations, over raw swipe or match volume.
Common mistakes
- Designing a generic dating-app clone without using anything unique to the platform's data.
- Ignoring the privacy conflict between dating and visibility to an existing friend network.
Likely follow-up questions
- How would you prevent existing friends from seeing someone's dating profile?
- How would you measure whether matches are leading to real connections, not just swipes?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop